Analogical Inference and Analogical Access.

Abstract

Analogy is a powerful technique in commonsense learning and reasoning. People use analogies in problem solving, in developing mental models of a new domain, and in communicating knowledge. To model these natural uses of analogy, we need to understand the whole process of analogizing from the first, starting with access and ending with drawing inferences or extracting a principle from an analogy. In this paper, I first review the structure-mapping theory of analogical processing and describe a simulation of the theory. I then extend this framework to accessing analogy. I discuss some recent research in our lab that suggests that the accessibility of an analogical match is governed by different factors from its inferential soundness. Finally, I consider some competing theoretical approaches to analogy and suggest an integrated architecture for analogical processing.

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Document Details

Document Type
Technical Report
Publication Date
Aug 04, 1987
Accession Number
ADA184345

Entities

People

  • Dedre Gentner

Organizations

  • University of Illinois Urbana–Champaign

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  • AI & ML
  • AI & ML - Information Retrieval